Public Policy

Public policy research increasingly leverages computational methods to analyze large datasets and improve decision-making. Current research focuses on using machine learning, including reinforcement learning and various neural network architectures, to model policy impacts, detect biases in algorithms used for policy implementation, and analyze large volumes of policy documents for trends and insights. This work aims to enhance transparency, accountability, and effectiveness in policy development and implementation, with applications ranging from healthcare and agriculture to climate change and AI regulation. The ultimate goal is to create more evidence-based, equitable, and efficient policies that better serve the public interest.